Due to intense competition and a shortage of labour, manufacturers will further automate their operations and introduce cutting-edge product lines and market strategies. The cornerstone of this advancement lies in manufacturers' capability to integrate real-time operational data with business data, leverage AI-driven data analytics for valuable insights and recommendations, enhance automation throughout supply chains and manufacturing processes, and empower staff with real-time information to make intelligent decisions promptly. The factory of the future will amalgamate data from interconnected equipment, workforce, and supply chain to provide instant recommendations, adjust production autonomously, and allocate resources to more valuable tasks.

What Are Intelligent Operations?

Intelligent operations involve integrating a manufacturer's information technology and operational technology with artificial intelligence and machine learning to create a seamless feedback mechanism for enhancing operations. Data from operational technology sources like factory production lines, specialized equipment, and Internet of Things sensors is merged with data from manufacturing execution systems, enterprise asset management systems, and various applications. This aggregated data is then analysed using AI, and the generated insights are used to automatically adjust operations. This constant feedback loop introduces automation into the production process, leading to increased efficiency and sustained improvement. Intelligent operations bridge the gap between a manufacturer's operational technology systems and information technology systems. Through the integration and analysis of data using AI-based analytics, information from various parts of the company is consolidated. Intelligent operations streamline menial tasks, such as condensing repair reports, allowing employees to focus on more strategic responsibilities. This advanced level of automation can only be achieved by leveraging AI-based analytics on unified data.

Understanding Intelligent Operations

In the majority of manufacturing firms, there exists disconnect between Information Technology (IT) and Operational Technology (OT) functions. IT encompasses software and hardware components that support business operations and safeguard data for various departments such as finance, procurement, sales, marketing, human resources, Manufacturing Execution Systems (MES), and the supply chain. On the other hand, OT comprises systems and machinery responsible for operating factory floors and production lines, including supervisory control and data acquisition (SCADA) systems, programmable logic controllers (PLCs), robots, digital twins, sensors, and Internet of Things (IoT) systems. Intelligent operations eliminate the barrier between IT and OT by integrating data from various sources including machines, parts, production lines, raw materials, and finished goods, as well as finance, procurement, and supply chain systems. This allows manufacturing companies to effectively address production bottlenecks, foresee potential machine failures, and enhance the performance of parts and products using sensor data. For instance, suppliers of component parts to automakers can leverage sensor data to analyse the real-world performance of their products.

Functionality of Intelligent Operations

Effective operations management begins by developing a digital twin, a virtual representation of the factory's production line that can be viewed on workstation monitors or mobile devices. This digital twin is created by attaching sensors to various factory equipment, including mills, welding stations, lathes, and robotic arms, as well as the finished products and components. These sensors gather data on key metrics like revolutions per minute, temperatures, throughput, and machine stability, which is then displayed on a visual explorer interface. This interface provides employees and supervisors with a comprehensive overview of the factory floor, allowing them to quickly identify and address issues such as malfunctioning equipment or deviations from production parameters. In Intelligent operations, artificial intelligence (AI) extracts information from operational technology (OT) systems within the intelligent factory, analyses it, and sends alerts to the information technology (IT) systems driving the business. These alerts can then trigger complex tasks automatically, eliminating the need for human intervention. Examples include autonomous production adjustments and ensuring technicians and operators have the necessary certifications for their assigned tasks. Intelligent operations establish an autonomous feedback loop of “sense, respond, decide, and do,” advancing manufacturing towards lights-out operations. Leveraging AI-based analytics on a unified cloud platform enables the collection, integration, and interpretation of operational data to orchestrate intricate tasks.

Traits of Intelligent Operations

Intelligent operations involve using a unified user interface that is equipped with all necessary tools for operators to effectively carry out their tasks. This integrated system has the capability to substitute conventional manufacturing execution systems, which typically lack seamless integration with other corporate systems. Intelligent operations are defined by four primary characteristics.

• Creating a smooth flow from design to production, efficient operations rely on a singular "digital thread" that integrates data from various stages and environments in the product lifecycle. This interconnectedness provides employees and managers with real-time insights into manufacturing activities occurring in the physical realm.
• Within Intelligent operations, data pertaining to manufacturing tasks, such as work orders, is connected to the corresponding business transactions, like customer orders. Utilizing a unified data model, intelligent operations harmonize business and production data, ensuring that all orders are manufactured to precise specifications to meet customer demand.
• Intelligent operations leverage AI-powered data analytics to provide unparalleled insights into key areas such as quality assurance/control, production line performance, product quality, and asset availability.
• Automated operations allow for swift implementation of changes from upstream sources, such as altered order priorities or production schedules. Likewise, identifying equipment failures promptly can impact upstream business processes, increasing productivity and empowering employees to make informed decisions.

Advantages of Implementing Intelligent Operations in Business

Manufacturers have the opportunity to enhance their competitive advantage by providing employees with timely access to accurate data and valuable insights. By implementing Intelligent operations, companies can boost employee engagement, enabling them to concentrate on enhancing processes that drive increased business value. The advantages of intelligent operations encompass.

• Enhanced overall operational efficiency through the implementation of Intelligent  operations, which enables manufacturers to boost productivity, improve quality, increase production visibility, and elevate factory output through continuous monitoring and feedback mechanisms.
• Enhanced employee recruitment and retention rates by automating routine tasks, allowing employees to focus on addressing larger business challenges, thereby increasing engagement and satisfaction among staff members who seek opportunities to contribute meaningfully.
• Strengthened supply chain resilience by leveraging AI-based analytics on operational and informational data to provide real-time alerts on potential disruptions, facilitating proactive adjustments to plans, suppliers, and logistics to minimize work stoppages and ensure operational continuity.
• Many manufacturers face challenges in adjusting production to match supply and demand signals, while also dealing with increasing material, labour, and overhead costs that impact profit margins. Implementing intelligent operations can help mitigate demand risks by providing faster alerts on potential disruptions in the supply chain, allowing for quicker responses and alternative arrangements. Additionally, intelligent operations can lower costs through enhanced automation, ultimately increasing profit margins.
• Intelligent operations also play a crucial role in maximizing capacity for manufacturers, enabling them to produce more products at a faster pace to meet growing demands. For instance, in scenarios where manufacturers aim to incorporate customization services into their existing products, intelligent operations can facilitate the automation necessary to fulfil customized orders promptly and accurately, as well as predict future maintenance needs.
• Continuous feedback through intelligent operations is essential for the company to achieve its sustainability targets and promptly address any deviation from these objectives. These targets for manufacturers typically involve minimizing energy and natural resource consumption, mitigating the environmental impact of products, and enhancing both employee and product safety.

Challenges in Implementing Intelligent Operations

One of the primary obstacles to efficient operations lies in the fact that a manufacturer’s Information Technology and Operational Technology are typically overseen by separate departments, each adhering to their own set of objectives. These departments may operate on individual networks and follow distinct procurement and budgeting protocols. Additional hurdles may include:

• Outdated applications, typically located on-premises, were often heavily customized but are now outdated, necessitating modifications to the underlying code. This technical workload hinders the rate of innovation.
• Manufacturers are faced with challenges in integrating their MES with the aforementioned digital thread, often resorting to disparate point solutions selected by different departments within the organization. This array of systems adds complexity and impedes efforts to streamline and automate operations.
• Disconnected solutions working independently of each other. For instance, product lifecycle management systems, where a majority of product design and development activities occur, are not effectively linked to the MES, slowing down enhancements to the end product.
• Maintenance activities operating separately from operations result in inefficient scheduling and decreased uptime for assets supplied or leased to customers.
• Complex and inconsistent user interfaces in IT and OT systems are commonly utilized to cater to the needs of the system rather than the users. These interfaces often hinder employees instead of facilitating them to perform their tasks more efficiently and quickly.

Future of Intelligent Operations

The concepts of intelligent operations can be applied outside of manufacturing. The closely related field of maintenance, for example, can benefit from the same capabilities for predicting when machines might fail and dispatching repair crews to prevent it. The data fed from assets in the field, such as cell phone towers and jet engines, can be used to improve these assets and increase uptime. Other product-centric industries can also apply intelligent operations ideas to their supply chains. In healthcare, for example, applying RFID tags to medical supplies and using automatic replenishment and robotic picking can deliver significant labour and cost savings while helping improve patient outcomes. Or a power company can use a digital twin to provide an exploded view of all the component parts inside a malfunctioning transformer, see precisely which part is failing, dispatch a repair crew, and even generate a purchase order for replacement parts.

Experience a Smart Future with Nirmalya Enterprise

Nirmalya Enterprise offers a comprehensive cloud-based manufacturing platform with intelligent operations, enhances Supply Chain & Manufacturing with advanced capabilities to improve operational performance and enable intelligent decision-making by the workforce. By merging real-time operational data with business data and leveraging advanced analytics, it provides recommendations, streamlines processes, and enhances automation throughout the supply chain and manufacturing operations. Nirmalya Enterprise Platform features a unified architecture with AI & ML capabilities, ensuring a seamless experience across its range of solutions. Combined with Nirmalya Business Intelligence and analytics, the platform offers manufacturing companies valuable insights, automated alerts, process automation, and an intuitive user interface designed to simplify workflows for employees.

Nirmalya Enterprise Platform offers mobile-based solutions for various enterprise functions such as supply chain management, human capital management, customer relationship management, manufacturing execution systems, warehouse management, MES, EHS, LMS, and enterprise asset management. By leveraging Nirmalya platform, enterprises can achieve increased connectivity and efficiency, leading to improved accuracy, productivity, and profitability.

To learn more about how enterprises are experiencing tangible benefits through the use of Nirmalya Enterprise Platform and Mobility, please reach out to us today.